↓ Skip to main content

Using Normalization Process Theory in feasibility studies and process evaluations of complex healthcare interventions: a systematic review

Overview of attention for article published in Implementation Science, June 2018
Altmetric Badge

About this Attention Score

  • In the top 5% of all research outputs scored by Altmetric
  • Among the highest-scoring outputs from this source (#33 of 1,821)
  • High Attention Score compared to outputs of the same age (96th percentile)
  • High Attention Score compared to outputs of the same age and source (97th percentile)

Mentioned by

twitter
144 X users
wikipedia
2 Wikipedia pages

Citations

dimensions_citation
384 Dimensions

Readers on

mendeley
707 Mendeley
You are seeing a free-to-access but limited selection of the activity Altmetric has collected about this research output. Click here to find out more.
Title
Using Normalization Process Theory in feasibility studies and process evaluations of complex healthcare interventions: a systematic review
Published in
Implementation Science, June 2018
DOI 10.1186/s13012-018-0758-1
Pubmed ID
Authors

Carl R. May, Amanda Cummings, Melissa Girling, Mike Bracher, Frances S. Mair, Christine M. May, Elizabeth Murray, Michelle Myall, Tim Rapley, Tracy Finch

Abstract

Normalization Process Theory (NPT) identifies, characterises and explains key mechanisms that promote and inhibit the implementation, embedding and integration of new health techniques, technologies and other complex interventions. A large body of literature that employs NPT to inform feasibility studies and process evaluations of complex healthcare interventions has now emerged. The aims of this review were to review this literature; to identify and characterise the uses and limits of NPT in research on the implementation and integration of healthcare interventions; and to explore NPT's contribution to understanding the dynamics of these processes. A qualitative systematic review was conducted. We searched Web of Science, Scopus and Google Scholar for articles with empirical data in peer-reviewed journals that cited either key papers presenting and developing NPT, or the NPT Online Toolkit ( www.normalizationprocess.org ). We included in the review only articles that used NPT as the primary approach to collection, analysis or reporting of data in studies of the implementation of healthcare techniques, technologies or other interventions. A structured data extraction instrument was used, and data were analysed qualitatively. Searches revealed 3322 citations. We show that after eliminating 2337 duplicates and broken or junk URLs, 985 were screened as titles and abstracts. Of these, 101 were excluded because they did not fit the inclusion criteria for the review. This left 884 articles for full-text screening. Of these, 754 did not fit the inclusion criteria for the review. This left 130 papers presenting results from 108 identifiable studies to be included in the review. NPT appears to provide researchers and practitioners with a conceptual vocabulary for rigorous studies of implementation processes. It identifies, characterises and explains empirically identifiable mechanisms that motivate and shape implementation processes. Taken together, these mean that analyses using NPT can effectively assist in the explanation of the success or failure of specific implementation projects. Ten percent of papers included critiques of some aspect of NPT, with those that did mainly focusing on its terminology. However, two studies critiqued NPT emphasis on agency, and one study critiqued NPT for its normative focus. This review demonstrates that researchers found NPT useful and applied it across a wide range of interventions. It has been effectively used to aid intervention development and implementation planning as well as evaluating and understanding implementation processes themselves. In particular, NPT appears to have offered a valuable set of conceptual tools to aid understanding of implementation as a dynamic process.

X Demographics

X Demographics

The data shown below were collected from the profiles of 144 X users who shared this research output. Click here to find out more about how the information was compiled.
Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 707 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 707 100%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 91 13%
Researcher 88 12%
Student > Master 84 12%
Student > Bachelor 53 7%
Student > Doctoral Student 38 5%
Other 128 18%
Unknown 225 32%
Readers by discipline Count As %
Medicine and Dentistry 117 17%
Nursing and Health Professions 111 16%
Social Sciences 58 8%
Psychology 52 7%
Business, Management and Accounting 19 3%
Other 94 13%
Unknown 256 36%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 83. This is our high-level measure of the quality and quantity of online attention that it has received. This Attention Score, as well as the ranking and number of research outputs shown below, was calculated when the research output was last mentioned on 10 June 2023.
All research outputs
#524,944
of 25,765,370 outputs
Outputs from Implementation Science
#33
of 1,821 outputs
Outputs of similar age
#11,346
of 343,386 outputs
Outputs of similar age from Implementation Science
#1
of 40 outputs
Altmetric has tracked 25,765,370 research outputs across all sources so far. Compared to these this one has done particularly well and is in the 97th percentile: it's in the top 5% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 1,821 research outputs from this source. They typically receive a lot more attention than average, with a mean Attention Score of 15.0. This one has done particularly well, scoring higher than 98% of its peers.
Older research outputs will score higher simply because they've had more time to accumulate mentions. To account for age we can compare this Altmetric Attention Score to the 343,386 tracked outputs that were published within six weeks on either side of this one in any source. This one has done particularly well, scoring higher than 96% of its contemporaries.
We're also able to compare this research output to 40 others from the same source and published within six weeks on either side of this one. This one has done particularly well, scoring higher than 97% of its contemporaries.